Master Class: GANS with Apps in Synthetic Data
With Gautier Marti discussing various innovations in neural networks, GANs are becoming popular as a means of generating synthetic data.
QuantUniversity partnered with PRMIA for QuantUniversity’s fall school in Machine Learning and AI in Finance. We had more than 1000 participants from more than 20 countries including India, China, Australia, UK, Turkey, South Africa etc. attend the our courses.
This fall, we are offering 3 courses in Data Science, Machine Learning, and Model Risk Management:
- Just Enough Python for Data Science
- Machine Learning and AI for Financial Professionals
- Model Risk Management for Machine Learning Models
In addition, we are hosting guest lectures from eminent quants, innovators, and thinkers on various topics in AI/ML and Fintech related topics.
Lecture 1
In Week 1, we had Gautier Marti and Sri Krishnamurthy from QuantUniversity discuss their work on GANS with Applications in Synthetic Data Generation. Here is a summary of the workshop.
Summary:
In this master class, Gautier discussed Generative Adversarial Networks (GANs) and discussed applications in synthetic data generation and other quantitative finance applications. He discussed his work on CORRGANS, Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks.[1]
Reference: 1. https://arxiv.org/abs/1910.09504
Listen to the Podcast here
Slides, demos, and videos at
https://academy.qusandbox.com/#/market/5f9834e199aa4a24691da81e
